Opinion Polarization Research Articles

To the Question of Building an Ideological Basis of the Legal Policy for the Criminal Sphere of Russian Society

The article examines the ideological basis of the legal policy for the criminal sphere of Russian society. The author notes that, in spite of optimistic criminological indices found in official statistics, it is too early to conclude that the criminal situation in the country is stable. It is stressed that the situation with law and order in modern Russia is far from ideal due to, largely, a lack of a sound criminal policy. The author assesses the contemporary condition of Russian criminal policy as a crisis and stresses that this crisis is, primarily, an ideological one. The paper states that in today’s Russia the question of developing any policy, including criminal policy, is very sensitive due to the polarization of opinions as to whether this process should rely on a radical modernization of its ideological basis or it should use national foundations while taking into account the existing traditions. Within this context, the author notes that the Russian state was historically based on a system of obligations placed on a person, and it still uses the idea of obligations and (or) the system of the Gospel’s Commandments. However, today this fundamental basis is eroded by the values of uncontrolled liberalism, which not only dictates permissiveness in all spheres of life, but also imposes this ideology as the only one possible. The author believes that this path is absolutely unacceptable for Russia because, unlike the Western civilization, that has successfully replaced morals with the law, the Orthodox civilization has always given priority to the moral norms. Based on the presented material, the author concludes that, while formulating the clauses of criminal legal policy in contemporary Russia, it is necessary to rely upon its specific national features, and that the ideological basis should not contradict basic values that have been developing in the society for thousands of years. This approach will benefit the lawfulness of citizens and will reduce the level of legal nihilism, which is a serious obstacle for the effective use of law.

Globalized fears, localized securities: ‘Terrorism’ in political polarization in a one-party state

Partisanship has become the dominant ideological incentive to political polarization. Likewise, the analytical association between polarization and the party system in electoral democracies has focused, in most of the existing literature, on political polarization, leaving aside authoritarian or semi-authoritarian contexts where a fair multi-party election is absent or dysfunctional. By collecting and analyzing online posts about international terrorism from Sina Weibo in China, between January 2011 and December 2016, this study proves the existence of opinion polarization on terrorism in China's digital media sphere. By categorizing the findings into two camps, ‘global war on terror discourse’ and ‘anti-imperialist narrative’, the study elucidates these polarized attitudes in terms of their acceptance, denial and decomposition of the global discourse of fears about terrorism. Drawing on our case study, the study then proposes an alternative explanation for the motivation/driver of mass polarization in digitally networked communication in China, identified as the effect of globalization and localization.

When Polls Disagree: How Competitive Results and Methodological Quality Shape Partisan Perceptions of Polls and Electoral Predictions

AbstractThis study leverages a survey experiment in the lead up to the 2016 U.S. presidential election to evaluate how partisan biases, poll results, and their methodological quality interact to shape people’s assessments of polling accuracy and electoral expectations. In a nationally representative sample, we find that individuals disproportionately find polls more credible when their preferred candidate is leading. Partisan biases are mitigated when the polls themselves vary in objective indicators of quality: while more educated respondents are more likely to identify high-quality polls accurately, low education respondents’ bias was reduced when they encountered polls with varying methodological quality. Finally, these moderators influence respondents’ electoral expectations as well. We discuss the implications for journalistic coverage of polls, public opinion, and political polarization.

Emotional foundations of the public climate change divide

The worldwide rise of climate skeptical political leaders endangers sorely needed political efforts to mitigate climate change. In addition, climate skepticism expressed by the political elites may spread to the electorate, thus ultimately affecting mitigation actions at the population level. It is crucial to better understand the psychological mechanisms underlying elite influences on public opinion formation and polarization. Here we show how affective processes contribute to these top-down influences using longitudinal data in the context of the 2016 U.S. presidential election. Findings revealed a general decrease in climate change beliefs immediately after the presidential election (November 2016). We moreover found an increase in positive emotions and a decrease in negative emotions toward the Republican Party after the election of President Trump. Most importantly, the positive emotional shift towards the Republican Party mediated the decrease in climate change beliefs: Individuals with pronounced increases in positive emotions toward the Republican Party most strongly reduced their belief in climate change after the presidential election. The effect was intensified among Republican partisans, pointing towards a mechanism underlying political polarization. Using data based on a major real-world political event, our findings illustrate how partisans update their beliefs by referring to the positions of relevant political authorities. We moreover demonstrate how emotions drive top-down influences of political leaders on partisans’ opinions and beliefs. Finally, our findings reveal how intensified emotions can contribute to the aggravation of the public climate change divide.

Modeling of the Public Opinion Polarization Process with the Considerations of Individual Heterogeneity and Dynamic Conformity

Nowadays, hot issues are likely become bipolar or multipolar after heated discussion on the Internet. This article is focused on the study of the polarization phenomenon and establishes a public opinion polarization model with the considerations of individual heterogeneity and dynamic conformity. At first, this article introduces the dynamic changing function of an individual’s conformity tendency to other’s attitudes in the interaction process. It further defines the influential weight between different interactive individuals, and expands the interactive individual from complete homogeneity to initial attitude heterogeneity, and finally, conformity heterogeneity. Then, through simulation experiments, we find that the degree of changing in individual attitude is limited. That is, it is difficult for the individuals who have one directional attitude at the initial time to change into another opposite attitude through interaction. In addition, individuals with low conformity within a certain threshold are more likely to form polarization. Finally, the rationality and effectiveness of the proposed model are verified by the typical case “Mimeng Event”.

Active Citizenship and Hate Speech on Social Media in the Context of Romanian Family Referendum

Active citizenship is one of the most interesting characteristics of young generations worldwide and is strongly connected to digital media usage. Internet gives people a voice to speak up about stressing community problems, unite in groups with the same views for a stronger impact and conduct true lobby campaigns to promote and sustain their ideas. However tangible, utopic or doubtful this democratic way of civic involvement may appear for a global digital community, its manifestation is still problematic, as it nurtures, in some cases, hate speech and extreme polarization of opinions. To support this idea, we conducted a study that analysed civic activism and the values promoted in the context of Romanian Family Referendum. Using a qualitative methodology based on communication sciences techniques and semiotic investigation, we analysed the type of discourse used in social media and the frequency of hate speech and undemocratic behaviour. At the end of this study, we will outline some concluding ideas regarding the discussed topic.

The Politicisation of the European Central Bank and the Bundestag

The European Central Bank (ECB) became one of the key actors during the Eurozone crisis. However, its prominent role was not without controversy. On one hand, the Eurozone was stabilised, no member state defaulted, and no state had to leave the Euro. On the other hand, the ECB had to stretch its mandate, expand its policy remit, and adopt so-called ‘unconventional’ monetary policies. These attempts to depoliticise political challenges through a technocratic approach reduced the opportunities for democratic contestation, but they also bred frustration that led to politicisation. This article studies to what extent this politicisation affected the perception of the ECB in national parliaments. For this purpose, it studies the extent to which ECB policy has become politicised in the German Bundestag through an analysis of plenary debates from 2005 to 2018. The Bundestag represents an unlikely case for politicisation despite wide-spread criticism of the ECB in the media, as Germany was traditionally attached to creating a highly independent ECB, until recently had no major Eurosceptic right-wing parties, and parliamentary scrutiny of the national central bank is low. However, by studying the salience of ECB policies, the polarisation of opinion in the parliament, as well as the range of actors participating in the debates, this article finds that the ECB’s policies have become politicised and the subject of scrutiny and dissatisfaction.

Thinking Fast and Furious: Emotional Intensity and Opinion Polarization in Online Media

AbstractHow do online media increase opinion polarization? The “echo chamber” thesis points to the role of selective exposure to homogeneous views and information. Critics of this view emphasize the potential of online media to expand the ideological spectrum that news consumers encounter. Embedded in this discussion is the assumption that online media affects public opinion via the range of information that it offers to users. We show that online media can induce opinion polarization even among users exposed to ideologically heterogeneous views, by heightening the emotional intensity of the content. Higher affective intensity provokes motivated reasoning, which in turn leads to opinion polarization. The results of an online experiment focusing on the comments section, a user-driven tool of communication whose effects on opinion formation remain poorly understood, show that participants randomly assigned to read an online news article with a user comments section subsequently express more extreme views on the topic of the article than a control group reading the same article without any comments. Consistent with expectations, this effect is driven by the emotional intensity of the comments, lending support to the idea that motivated reasoning is the mechanism behind this effect.

An Insight of Opinion Mining on Hotel Reviews

The web has altered the way the humans express opinions on various products or services. We can also share our experience about various services used. Internet era has changed the way of thinking , various platforms on the web are the convenient way of sharing thoughts and knowledge. Opinion mining is a method that classifies human emotions into positive, negative and neutral sentiments. Mining of opinions can be done on the basis of document, sentence and aspects. This paper reviews the various algorithms and techniques used for opinion mining. Here we have focused on opinion mining based on features of hotels like food, transportation, room amenities etc. which enables us to determine the polarity of features of the various reviews of hotel. The recognition of polarity of opinions helps the hotels to promote their services and can plan marketing strategies accordingly.

A Distance Measure for the Analysis of Polar Opinion Dynamics in Social Networks

Analysis of opinion dynamics in social networks plays an important role in today’s life. For predicting users’ political preference, it is particularly important to be able to analyze the dynamics of competing polar opinions, such as pro-Democrat vs. pro-Republican. While observing the evolution of polar opinions in a social network over time, can we tell when the network evolved abnormally? Furthermore, can we predict how the opinions of the users will change in the future? To answer such questions, it is insufficient to study individual user behavior, since opinions can spread beyond users’ ego-networks. Instead, we need to consider the opinion dynamics of all users simultaneously and capture the connection between the individuals’ behavior and the global evolution pattern of the social network. In this work, we introduce the Social Network Distance (SND)—a distance measure that quantifies the likelihood of evolution of one snapshot of a social network into another snapshot under a chosen model of polar opinion dynamics. SND has a rich semantics of a transportation problem, yet, is computable in time linear in the number of users and, as such, is applicable to large-scale online social networks. In our experiments with synthetic and Twitter data, we demonstrate the utility of our distance measure for anomalous event detection. It achieves a true positive rate of 0.83, twice as high as that of alternatives. The same predictions presented in precision-recall space show that SND retains perfect precision for recall up to 0.2. Its precision then decreases while maintaining more than 2-fold improvement over alternatives for recall up to 0.95. When used for opinion prediction in Twitter data, SND’s accuracy is 75.6%, which is 7.5% higher than that of the next best method.

Aspect-based sentiment analysis based on dynamic attention GRU

Aspect-level sentiment analysis is a fine-grained task that aims to identify the sentiment polarity (i.e., negative, neutral, or positive) of a specific target opinion in its context. Since the sentiment polarity of a target depends on the target itself and the semantics of the context, the target and the sentence should be treated equally and modeled interactively. For aspect-level sentiment analysis, we propose (1) a method to encode the aspect and sentence simultaneously, and (2) a neural network based on a dynamic attention gated recurrent unit. The simultaneous encoding manner can generate the target representation, which contains more contextual clues. The dynamic attention mechanism can achieve the attention values of contextual words and further generate the target representation dynamically. Experimental results achieved on a SemEval 2014 dataset (Laptop and Restaurant) show that our approach achieves a significant improvement in the accuracy rates over the standard attention-based models.

Sentiment Analysis of Novel Review Using Long Short-Term Memory Method

The rapid development of the internet and social media and a large amount of text data has become an important research subject in obtaining information from the text data. In recent years, there has been an increase in research on sentiment analysis in the review text to determine the polarity of opinion on social media. However, there are still few studies that apply the deep learning method, namely Long Short-Term Memory for sentiment analysis in Indonesian texts.This study aims to classify Indonesian novel novels based on positive, neutral and negative sentiments using the Long Short-Term Memory (LSTM) method. The dataset used is a review of Indonesian language novels taken from the goodreads.com site. In the testing process, the LSTM method will be compared with the Naïve Bayes method based on the calculation of the values of accuracy, precision, recall, f-measure.Based on the test results show that the Long Short-Term Memory method has better accuracy results than the Naïve Bayes method with an accuracy value of 72.85%, 73% precision, 72% recall, and 72% f-measure compared to the results of the Naïve Bayes method accuracy with accuracy value of 67.88%, precision 69%, recall 68%, and f-measure 68%.

Продление срока срочного трудового договора: некоторые теоретические и практические вопросы

The problem of introducing changes to a fixed-term employment contract in terms of amending (extending) its term is an urgent applied problem in the work of personnel services, which often arises in the course of their practical work. Argued, based on established judicial practice, the solution to this problem will create clarity in the application of the norms of the Labor Code of the Russian Federation.
 The norms of the Labor Code of the Russian Federation do not contain a ban on the application of the provisions of art. 72 of the Labor Code of the Russian Federation. However, to date there is no single, reasoned opinion on whether it is possible to change the term of a fixed-term employment contract, and if possible, under what conditions? On this issue, there are polar opinions. Both the courts and state authorities have repeatedly changed their position on this issue, right up to the diametrically opposite.
 In this paper, the author attempts to answer this question on the basis of the existing judicial practice and the courts understand the relevant provisions of the Labor Code of the Russian Federation, the opinions of the federal authorities of the Russian Federation, as well as their own attempts to interpret the provisions of the law, and concludes that the term of a fixed-term labor contract in the presence of compliance with the necessary conditions dictated by the norms of the Labor Code of the Russian Federation, established law enforcement practice.

Immigrant sentiment and labour market vulnerability: economic perceptions of immigration in dualized labour markets

Recent years have seen an increase in concerns that labour market vulnerability and national economic performance might be interacting to foment more polarized opinions about immigration. This article uses European Social Survey and EU-SILC data from 23 countries to explore this potential relationship, examining attitudes about the economic impact of immigration. In doing so, it seeks to investigate how the link between labour market vulnerability and anti-immigrant sentiment may be shaped by both resource scarcity (in the economy as a whole) and job scarcity (on the labour market). Findings from the analysis are twofold. First, labour market vulnerability is indeed correlated with more negative beliefs about the economic contribution of immigrants, even controlling for related factors such as education and contract type. Second, this effect is moderated by GDP per capita (though not unemployment rates), with labour market insiders and outsiders holding more distinct attitudes in higher GDP countries; thus, although attitudes towards the economic contribution of immigrants are generally more negative in poorer countries, labour market vulnerability contributes to greater opinion polarization in stronger economies. It is therefore resource availability in the economy, rather than on the labour market, that appears to be crucial.

Party v. The People: Testing corrective action and supportive engagement in a partisan political context

ABSTRACTToday’s audiences have an opportunity to hear the political opinions of a more diverse sample of voters through online comment sections. Two theories suggest that the hostile or supportive climate created by peers will influence the audience’s engagement with comment sections. Corrective action hypothesis posits that citizens will engage offline and online when they perceive a hostile opinion climate. Meanwhile, the supportive-based engagement theory suggests that some audience members will be more likely to participate when a homogenous opinion climate speeds opinion crystallization. This study extends the engagement literature to the opinion climate created by online comments by investigating the interaction between political partisanship and the hostility of comments about a political candidate. In a 3 (political party congruence) X 3 (level of comment hostility) controlled experiment (N = 350), party identification of a candidate and the hostility of comments were manipulated. The change in opinion about the candidate and the likelihood of expressing a public opinion were measured. Results indicate the audience is most likely to express an opinion when the candidate and the audience member share party identification. Further, the study finds an interaction so that hostile opinion climate increased opinion polarization. Results suggest that audiences are more likely to support a fellow partisan being attacked than to attack a member of the political outgroup who is being supported. Finally, it finds the perception that comments will influence others has a role in opinion change and likelihood of expressing an opinion.

The evolution of polarization in the legislative branch of government.

The polarization of political opinions among members of the US legislative chambers measured by their voting records is greater today than it was 30 years ago. Previous research efforts to find causes of such increase have suggested diverse contributors, like growth of online media, echo chamber effects, media biases or disinformation propagation. Yet, we lack theoretic tools to understand, quantify and predict the emergence of high political polarization among voters and their legislators. Here, we analyse millions of roll-call votes cast in the US Congress over the past six decades. Our analysis reveals the critical change of polarization patterns that started at the end of 1980s. In earlier decades, polarization within each Congress tended to decrease with time. By contrast, in recent decades, the polarization has been likely to grow within each term. To shed light on the reasons for this change, we introduce here a formal model for competitive dynamics to quantify the evolution of polarization patterns in the legislative branch of the US government. Our model represents dynamics of polarization, enabling us to successfully predict the direction of polarization changes in 28 out of 30 US Congresses elected in the past six decades. From the evolution of polarization level as measured by the Rice index, our model extracts a hidden parameter–polarization utility which determines the convergence point of the polarization evolution. The increase in the polarization utility implied by the model strongly correlates with two current trends: growing polarization of voters and increasing influence of election campaign donors. Two largest peaks of the model’s polarization utility correlate with significant political or legislative changes happening at the same time.

Intelligent Opinion Polarity and Analysis in Discovering Product Related Customer Reviews A Survey

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

Analyzing the effect of location, communication regime, and demographic faultline on team cohesion

Purpose Building on the Lau and Murnighan’s theory of fault line strength, Flache and Mäs (2008b) proposed a computational opinion dynamics model to explore the effect of demographic fault line strength on team cohesion. This study aims to extend the Flache–Mäs (FM) model to incorporate geographical location and the dyadic communication regime in opinion formation process. More specifically, we make spatially proximate agents more likely to interact with each other in the dyadic communication regime. Our results show that when agents update their opinion after each pairwise encounter, opinion polarization is lower at steady state compared to when they update their opinion after interacting with all agents. In addition, if nearby agents are more likely to interact with each other, we see greater polarization compared to the FM model with the dyadic communication regime. An immediate policy implication of this result is that organizational managers should design work space in a way that encourage wider communications between members of a team and avoid geographically local communication. Design/methodology/approach We introduce our computational models to study the effect of location and the dyadic communication regime on team performance (as measured by agents’ opinions on various work-related issues) in the presence of a strong demographic fault line. Our models are extensions of the FM model. For clarification purposes, first we describe the FM model and then elaborate our extensions. Findings The most important finding of this paper is that the timing of interactions plays an important role in steady state of opinion space in a given population. The reason can be traced to the path-dependent nature of social systems, in which initial adopters of a certain opinion or an ideology can significantly change the final configuration of a population. For example, if an early adopter of a given work-related issue in an organization has an extremely positive view toward that issue, and s/he interacts with nearby employees who have similar demographic attributes, we would expect to find an extreme opinion cluster with respect to that issue after a while. However, depending on factors that affect the timing of interaction between individuals, we would expect different outcome in the same organization. If, for instance, more extreme people are more likely to interact, the results would be different compared to when moderate agents are more likely to interact. Originality/value One immediate policy implication of the results of this paper is that organizational managers should design work space in a way that encourage wider communications between members of a team and avoid geographically local communication, if they are to temper the negative effect of a strong demographic fault line. However, they should be cautious and take other related findings into account to avoid undesirable outcomes. For example, according to Flache and Mäss’s results, managers can also initially encourage discussion within demographically homogenous groups and avoid controversial work-related issues. In addition, previous studies showed that more contacts between agents may increase opinion polarization. Our results provide no evidence for more complex and modern organizational designs where individuals or teams do not have a fixed location or stable geographical pattern. For instance, in a modern car manufacturing shop floor, it is possible that workers have to move with cars, or operational engineers have to move between different sections and places. Furthermore, there may be a flexible and dynamic work schedule for workers such that they share a same work station but in different time, which requires a more complex model than what we presented in this paper. In this sense, the geographical setting analyzed in this paper should not be generalized to all organizations or companies. We also have no evidence about other critical factors that might affect the communication and activation regime of individuals. For example, one could imagine a case that workers with the same level of skill in a specific work-related issue are more likely to interact with each other. Moreover, some specific organizational structures could impose additional restrictions on who can/should interact with whom.

Echoslamming: how incivility interacts with cyberbalkanization on the social media in Hong Kong

ABSTRACTCyberbalkanization has growingly become common on the Internet and can lead to public’s opinion polarization. This study investigates a specific process of cyberbalkanization through which incivility is circulated within online communities. From a dataset of Hong Kong-based Facebook Pages collected during a social movement, a set of politically-organized communities was identified and their connectivity generated a post-sharing network. A random sample of contents shared between and within these communities was then manually classified based on the level of incivility. The targets of offence through the use of uncivil language were also coded. Contents shared within ideologically compatible communities were found to be more likely to be uncivil. The association was significantly more positive in a populistic community, of which members had unique political nature and cultural norms. The targets were usually political opponents and incivility was adopted to petition detractors from within-community discussions. We therefore suggest ‘echoslamming’ is an online phenomenon through which uncivil contents catalyse anger toward political opponents among ideologically congruent information sources and consequently reinforce the audience’s predilection. Such a mechanism can be one underlying explanation for a vicious circle of cyberbalkanization-induced polarization on political opinions.

Examining Opinion Polarization on Social Media Platform Using a Natural Experiment

In recent years, there is a heated discussion on opinion polarization on social media platforms. In this paper, we formulate a hierarchical Bayesian learning model to investigate the dynamics of individual opinion formation, particularly opinion polarization, on a social media platform where individuals are exposed to two sources of social influence: preceding peer microblogs in a microblog chain and comments from general public. We leverage a unique natural experiment contained in the data from a leading microblogging website in China on which comment function was shut down for three days. This setting allows us to identify the impact of comments from that of peer microblogs. We find that shutting down comment function reduces the sentiment polarization on the microblogging site. In addition, this effect is more significant for individuals with higher social media participation. Results of this study shed light on how to identify key users and how to conduct successful social media campaigns.